Reinforcement learning noob here

Recently I ve searching about Reinforcement deeplearning ,and I discoverd microsoft malmo project

malmo project provides some interface to control the actor in minecraft and get some feedback

tensorforce project provides Reinforcement learning api based on tensorflow

so my goal is to use tensorforce to play minecraft via malmo

In my opinion:
in tensorforce,I need to pass state to the agent ,and get the action from agent

    action = agent.act(state)
    state, terminal, reward = environment.execute(action)

then pass action to malmo (parse to command) and get the state (maybe world_state.observations)

    world_state = agent_host.getWorldState()
    obvsText = world_state.observations[-1].text

but how ? I dont know .and doing research now.
I really need some advice :mage:

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I barely know how to tame an Ocelot in Minecraft, this stuff you speak of sounds like witchcraft…